import sys
import os
import importlib

sys.path.insert(0, os.path.abspath("."))

import c302

import neuroml.writers as writers

range_incl = lambda start, end: range(start, end + 1)


def setup(
    parameter_set,
    generate=False,
    duration=2000,
    dt=0.05,
    target_directory="examples",
    data_reader="UpdatedSpreadsheetDataReader2",
    param_overrides={},
    verbose=True,
    config_param_overrides={},
):
    ParameterisedModel = getattr(
        importlib.import_module("c302.parameters_%s" % parameter_set),
        "ParameterisedModel",
    )
    params = ParameterisedModel()

    params.set_bioparameter(
        "unphysiological_offset_current", "0pA", "Testing TapWithdrawal", "0"
    )
    params.set_bioparameter(
        "unphysiological_offset_current_del", "0 ms", "Testing TapWithdrawal", "0"
    )
    params.set_bioparameter(
        "unphysiological_offset_current_dur", "2000 ms", "Testing TapWithdrawal", "0"
    )

    """
    VA_motors = ["VA%s" % c for c in range_incl(1, 12)]
    DA_motors = ["DA%s" % c for c in range_incl(1, 9)]
    AS_motors = ["AS%s" % c for c in range_incl(1, 11)]"""
    VB_motors = ["VB%s" % c for c in range_incl(1, 11)]
    DB_motors = ["DB%s" % c for c in range_incl(1, 7)]
    DD_motors = ["DD%s" % c for c in range_incl(1, 6)]
    VD_motors = ["VD%s" % c for c in range_incl(1, 13)]

    cells = list(["AVBL", "AVBR"] + DB_motors + VD_motors + VB_motors + DD_motors)

    muscles_to_include = True

    cells_to_stimulate = []

    cells_to_plot = list(cells)
    reference = "c302_%s_FW" % parameter_set

    conns_to_include = []
    conns_to_exclude = [
        "VB2-VB4_GJ",
        "VB4-VB2_GJ",
    ]
    conn_polarity_override = {
        r"^DB\d+-DD\d+$": "inh",
        r"^VB\d+-VD\d+$": "inh",
    }
    conn_number_override = {
        "^.+-.+$": 1,
    }

    input_list = []

    """dur = '250ms'
    amp = '3pA'
    for muscle_num in range(24):
        mdlx = 'MDL0%s' % (muscle_num + 1)
        mdrx = 'MDR0%s' % (muscle_num + 1)
        #mvlx = 'MVL0%s' % (muscle_num + 1)
        #mvrx = 'MVR0%s' % (muscle_num + 1)
        
        if muscle_num >= 9:
            mdlx = 'MDL%s' % (muscle_num + 1)
            mdrx = 'MDR%s' % (muscle_num + 1)
            #mvlx = 'MVL%s' % (muscle_num + 1)
            #mvrx = 'MVR%s' % (muscle_num + 1)

        
        startd = '%sms' % (muscle_num * 10)
        #startv = '%sms' % ((stim_num * 800 + 400) + muscle_num * 30)
        
        input_list.append((mdlx, startd, dur, amp))
        input_list.append((mdrx, startd, dur, amp))"""

    input_list.append(("MVR10", "0ms", "150ms", "1pA"))
    input_list.append(("MVR11", "0ms", "150ms", "2pA"))
    input_list.append(("MVR12", "0ms", "150ms", "3pA"))
    input_list.append(("MVR13", "0ms", "150ms", "3pA"))
    input_list.append(("MVR14", "0ms", "150ms", "2pA"))
    input_list.append(("MVR15", "0ms", "150ms", "1pA"))

    input_list.append(("MVL10", "0ms", "150ms", "1pA"))
    input_list.append(("MVL11", "0ms", "150ms", "2pA"))
    input_list.append(("MVL12", "0ms", "150ms", "3pA"))
    input_list.append(("MVL13", "0ms", "150ms", "3pA"))
    input_list.append(("MVL14", "0ms", "150ms", "2pA"))
    input_list.append(("MVL15", "0ms", "150ms", "1pA"))

    input_list.append(("MDL21", "0ms", "250ms", "3pA"))
    input_list.append(("MDL22", "0ms", "250ms", "3pA"))
    input_list.append(("MDR21", "0ms", "250ms", "3pA"))
    input_list.append(("MDR22", "0ms", "250ms", "3pA"))

    amp = "4pA"
    dur = "250ms"

    for stim_num in range(15):
        for muscle_num in range(7):
            mdlx = "MDL0%s" % (muscle_num + 1)
            mdrx = "MDR0%s" % (muscle_num + 1)
            mvlx = "MVL0%s" % (muscle_num + 1)
            mvrx = "MVR0%s" % (muscle_num + 1)

            if muscle_num >= 9:
                mdlx = "MDL%s" % (muscle_num + 1)
                mdrx = "MDR%s" % (muscle_num + 1)
                mvlx = "MVL%s" % (muscle_num + 1)
                mvrx = "MVR%s" % (muscle_num + 1)

            startd = "%sms" % (stim_num * 800 + muscle_num * 30)
            startv = "%sms" % ((stim_num * 800 + 400) + muscle_num * 30)

            input_list.append((mdlx, startd, dur, amp))
            input_list.append((mdrx, startd, dur, amp))
            if muscle_num != 6:
                input_list.append((mvlx, startv, dur, amp))
                input_list.append((mvrx, startv, dur, amp))

    d_v_delay = 400

    start = 190
    motor_dur = "250ms"

    input_list.append(("AVBL", "0ms", "1e9ms", "15pA"))
    input_list.append(("AVBR", "0ms", "1e9ms", "15pA"))
    input_list.append(("DB1", "%sms" % (start), motor_dur, "3pA"))
    input_list.append(("VB1", "%sms" % (start + d_v_delay), motor_dur, "3pA"))

    i = start + 2 * d_v_delay
    j = start + 3 * d_v_delay
    for pulse_num in range(1, 15):
        input_list.append(("DB1", "%sms" % i, motor_dur, "3pA"))
        input_list.append(("VB1", "%sms" % j, motor_dur, "3pA"))
        i += d_v_delay * 2
        j += d_v_delay * 2

    # input_list = []
    # input_list.append(('AVBL', '0ms', '1900ms', '15pA'))
    # input_list.append(('AVBR', '0ms', '1900ms', '15pA'))

    config_param_overrides["input"] = input_list

    param_overrides = {
        "mirrored_elec_conn_params": {
            r"^AVB._to_DB\d+\_GJ$_elec_syn_gbase": "0.001 nS",
            r"^AVB._to_VB\d+\_GJ$_elec_syn_gbase": "0.001 nS",
            r"^DB\d+_to_DB\d+\_GJ$_elec_syn_gbase": "0.001 nS",
            #'^DB\d+_to_DB\d+\_GJ$_elec_syn_p_gbase': '0.08 nS',
            #'^DB\d+_to_DB\d+\_GJ$_elec_syn_sigma': '0.2 per_mV',
            #'^DB\d+_to_DB\d+\_GJ$_elec_syn_mu': '-20 mV',
            r"^VB\d+_to_VB\d+\_GJ$_elec_syn_gbase": "0.001 nS",
            #'^VB\d+_to_VB\d+\_GJ$_elec_syn_p_gbase': '0.1 nS',
            #'^VB\d+_to_VB\d+\_GJ$_elec_syn_sigma': '0.3 per_mV',
            #'^VB\d+_to_VB\d+\_GJ$_elec_syn_mu': '-30 mV',
            #'VB2_to_VB4_elec_syn_gbase': '0 nS',
            r"^DB\d+_to_VB\d+\_GJ$_elec_syn_gbase": "0 nS",
            r"^DB\d+_to_DD\d+\_GJ$_elec_syn_gbase": "0 nS",
            r"^VB\d+_to_VD\d+\_GJ$_elec_syn_gbase": "0 nS",
            #'^VD\d+_to_DD\d+\_GJ$_elec_syn_gbase': '0 nS',
            "DD1_to_MVL08_elec_syn_gbase": "0 nS",
            "VD2_to_MDL09_elec_syn_gbase": "0 nS",
        },
        r"^VB\d+_to_VB\d+$_exc_syn_conductance": "18 nS",
        r"^VB\d+_to_VB\d+$_exc_syn_ar": "0.19 per_s",
        r"^VB\d+_to_VB\d+$_exc_syn_ad": "73 per_s",
        r"^VB\d+_to_VB\d+$_exc_syn_beta": "2.81 per_mV",
        r"^VB\d+_to_VB\d+$_exc_syn_vth": "-22 mV",
        r"^VB\d+_to_VB\d+$_exc_syn_erev": "10 mV",
        r"^DB\d+_to_DB\d+$_exc_syn_conductance": "20 nS",
        r"^DB\d+_to_DB\d+$_exc_syn_ar": "0.08 per_s",
        r"^DB\d+_to_DB\d+$_exc_syn_ad": "18 per_s",
        r"^DB\d+_to_DB\d+$_exc_syn_beta": "0.21 per_mV",
        r"^DB\d+_to_DB\d+$_exc_syn_vth": "-10 mV",
        r"^DB\d+_to_DB\d+$_exc_syn_erev": "10 mV",
        "initial_memb_pot": "-50 mV",
        "AVBR_to_DB4_exc_syn_conductance": "0 nS",
        #'VB4_to_VB5_exc_syn_conductance': '0 nS',
        "AVBL_to_VB2_exc_syn_conductance": "0 nS",
        "AVBR_to_VD3_exc_syn_conductance": "0 nS",
        #'^DB\d+_to_DD\d+$_exc_syn_conductance': '0 nS',
        #'^DD\d+_to_DB\d+$_inh_syn_conductance': '0 nS',
        #'^VB\d+_to_VD\d+$_exc_syn_conductance': '0 nS',
        #'^VD\d+_to_VB\d+$_inh_syn_conductance': '0 nS',
        "DD1_to_VB2_inh_syn_conductance": "0 nS",
        "neuron_to_muscle_exc_syn_conductance": "0.5 nS",
        r"^DB\d+_to_MDL\d+$_exc_syn_conductance": "0.4 nS",
        r"^DB\d+_to_MDR\d+$_exc_syn_conductance": "0.4 nS",
        r"^VB\d+_to_MVL\d+$_exc_syn_conductance": "0.6 nS",
        r"^VB\d+_to_MVR\d+$_exc_syn_conductance": "0.6 nS",
        "neuron_to_muscle_exc_syn_vth": "37 mV",
        "neuron_to_muscle_inh_syn_conductance": "0.6 nS",
        "neuron_to_neuron_inh_syn_conductance": "0.2 nS",
        #'DB2_to_MDL11_exc_syn_conductance': '1 nS',
        "AVBR_to_MVL16_exc_syn_conductance": "0 nS",
        "ca_conc_decay_time_muscle": "60.8 ms",
        "ca_conc_rho_muscle": "0.002338919 mol_per_m_per_A_per_s",
    }

    nml_doc = None
    if generate:
        nml_doc = c302.generate(
            reference,
            params,
            cells=cells,
            cells_to_plot=cells_to_plot,
            cells_to_stimulate=cells_to_stimulate,
            conns_to_include=conns_to_include,
            conns_to_exclude=conns_to_exclude,
            conn_polarity_override=conn_polarity_override,
            conn_number_override=conn_number_override,
            muscles_to_include=muscles_to_include,
            duration=duration,
            dt=dt,
            target_directory=target_directory,
            data_reader=data_reader,
            param_overrides=param_overrides,
            verbose=verbose,
        )

        # if config_param_overrides.has_key('input'):
        #    input_list = config_param_overrides['input']

        for stim_input in input_list:
            cell, start, dur, current = stim_input
            c302.add_new_input(nml_doc, cell, start, dur, current, params)

        nml_file = target_directory + "/" + reference + ".net.nml"
        writers.NeuroMLWriter.write(
            nml_doc, nml_file
        )  # Write over network file written above...

        c302.print_("(Re)written network file to: " + nml_file)

    return cells, cells_to_stimulate, params, muscles_to_include, nml_doc


if __name__ == "__main__":
    parameter_set = sys.argv[1] if len(sys.argv) == 2 else "C2"
    data_reader = sys.argv[2] if len(sys.argv) == 3 else "UpdatedSpreadsheetDataReader2"

    setup(parameter_set, generate=True, data_reader=data_reader)
